Adaptive Subsurface 3-D Imaging Based on Peak Phase-Retrieval and Complex-Valued Self-Organizing Map

We propose an adaptive subsurface 3-D visualization system based on a complex-valued self-organizing map (CSOM). Conventionally buried things can be detected in the so-called B-scan images obtained by a ground penetrating radar. In contrast, our proposed method is able not only to detect their presence but also to classify the targets by the self-organizing dynamics in the CSOM. Instead of utilizing only the amplitude information in the time domain, we use both the amplitude and the phase information to obtain the scattering coefficients of scatterers by use of the phase retrieval method.